Loading...
Stream Processing
Distributed Stream Processing Framework
★ 4.0
Distributed Event Streaming Platform
★ 4.8
N/A — Java-basedpip install confluent-kafkaN/A — Java-basedpip install confluent-kafkaPython data engineers interact with Apache Samza primarily through its REST API or by bridging Python logic into Samza jobs via subprocess calls. More commonly, Python pipelines produce events to Kafka topics that Samza jobs consume for stateful aggregation — Python handles data ingestion and enrichment while Samza manages low-latency stateful stream processing at scale.
Python data engineers use `confluent-kafka-python` or `kafka-python` to produce events to topics and consume them in real-time. A common pattern is a Faust or plain consumer loop that reads messages, transforms them with pandas or Pydantic, and writes results to a database or another topic. Kafka is the backbone of event-driven data architectures in Python shops.
Individual Tool Pages